
本策略是一个基于Elder’s力量指数(EFI)的量化交易系统,结合了标准差和移动平均线进行信号判断,并使用ATR动态调整止损止盈位置。该策略通过计算快速和慢速EFI指标,并将其标准化后进行交叉信号判断,实现了一个完整的交易系统。策略采用了动态止损和追踪止盈机制,有效控制风险的同时追求更大收益。
策略主要基于以下几个核心要素构建: 1. 使用两个不同周期(13和50)的EFI指标计算快速和慢速力量指数 2. 对两个周期的EFI进行标准差归一化处理,使信号更具有统计意义 3. 当快速和慢速EFI同时突破上方标准差时,触发做多信号 4. 当快速和慢速EFI同时突破下方标准差时,触发做空信号 5. 使用ATR动态设置止损位置,并随着价格变动调整止损位置 6. 采用基于ATR的追踪止盈机制,在保护利润的同时让利润继续增长
该策略通过结合EFI指标、标准差和ATR,构建了一个完整的交易系统。策略的优势在于信号系统可靠性高,风险控制合理,但仍需要针对不同市场环境进行优化。通过增加市场环境判断、成交量过滤等机制,可以进一步提高策略的稳定性和收益性。整体而言,该策略提供了一个良好的量化交易框架,具有较好的实用价值。
/*backtest
start: 2019-12-23 08:00:00
end: 2024-11-27 00:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=5
strategy("Elder's Force Index Strategy with ATR-Based SL and TP", overlay=true)
// Input parameters for fast and long EFI
efi_fast_length = input.int(13, "Fast EFI Length", minval=1)
efi_long_length = input.int(50, "Long EFI Length", minval=1)
stdev_length = input.int(50, "Standard Deviation Length", minval=2, maxval=300)
numdev = input.float(2, "Number of Deviations", minval=1, maxval=20, step=0.1)
atr_length = input.int(14, "ATR Length", minval=1)
atr_multiplier_sl = input.float(1.5, "ATR Multiplier for Stop Loss", step=0.1)
trailing_tp_multiplier = input.float(0.5, "Multiplier for Trailing Take Profit", step=0.1)
// Elder's Force Index Calculation for Fast and Long EFI
efi_fast = ta.ema((close - close[1]) * volume, efi_fast_length)
efi_long = ta.ema((close - close[1]) * volume, efi_long_length)
// Calculate Standard Deviation for Fast EFI
efi_fast_average = ta.sma(efi_fast, stdev_length)
efi_fast_stdev = ta.stdev(efi_fast, stdev_length)
efi_fast_diff = efi_fast - efi_fast_average
efi_fast_result = efi_fast_diff / efi_fast_stdev
// Calculate Standard Deviation for Long EFI
efi_long_average = ta.sma(efi_long, stdev_length)
efi_long_stdev = ta.stdev(efi_long, stdev_length)
efi_long_diff = efi_long - efi_long_average
efi_long_result = efi_long_diff / efi_long_stdev
// Define upper and lower standard deviation levels
upper_sd = numdev
lower_sd = -numdev
// Define entry conditions based on crossing upper and lower standard deviations
long_condition = efi_fast_result > upper_sd and efi_long_result > upper_sd
short_condition = efi_fast_result < lower_sd and efi_long_result < lower_sd
// Check if a position is already open
is_position_open = strategy.position_size != 0
// Calculate ATR for stop loss and take profit
atr = ta.atr(atr_length)
// Initialize stop loss and take profit variables
var float stop_loss = na
var float take_profit = na
// Execute trades based on conditions, ensuring only one trade at a time
if (long_condition and not is_position_open)
strategy.entry("Long", strategy.long)
stop_loss := close - atr * atr_multiplier_sl // Set initial stop loss based on ATR
take_profit := close + atr * trailing_tp_multiplier // Set initial take profit based on ATR
if (short_condition and not is_position_open)
strategy.entry("Short", strategy.short)
stop_loss := close + atr * atr_multiplier_sl // Set initial stop loss based on ATR
take_profit := close - atr * trailing_tp_multiplier // Set initial take profit based on ATR
// Update exit conditions
if (is_position_open)
// Update stop loss for trailing
if (strategy.position_size > 0) // For long positions
stop_loss := math.max(stop_loss, close - atr * atr_multiplier_sl)
// Adjust take profit based on price movement
take_profit := math.max(take_profit, close + atr * trailing_tp_multiplier)
else if (strategy.position_size < 0) // For short positions
stop_loss := math.min(stop_loss, close + atr * atr_multiplier_sl)
// Adjust take profit based on price movement
take_profit := math.min(take_profit, close - atr * trailing_tp_multiplier)
// Set exit conditions
strategy.exit("Long Exit", from_entry="Long", stop=stop_loss, limit=take_profit)
strategy.exit("Short Exit", from_entry="Short", stop=stop_loss, limit=take_profit)